What skills will set you apart in the age of automation?

Robots may be able to beat us at chess, but they still have trouble when it comes to soft skills — making sense of human behavior.

What skills will set you apart in the age of automation?

DAVID EPSTEIN: In a rapidly changing work world it's important to be a constant learner, to be able to change and evolve your skills. Especially when we're facing automation of certain types of work. So, I want you to think about a spectrum of work that gets automated. On one part of the spectrum is chess. Chess is based on rules. It's very clear. Patterns repeat. That is a great situation for a computer. Computers are really good at patterns which is why they made exponential progress in chess and now the chess app on your iPhone can beat the best human chess player in the world.

In the middle of the spectrum maybe think about self-driving cars. Self-driving cars we've made great progress. There are rules of the road so they're regular repeating patterns, but there are some significant challenges that remain. And on the far end of the spectrum we have something like say cancer research where IBM's Watson had a lot of hype but actually was underperformed at hype in such a way that when I talk to AI researchers some of them were worried that it would damage the reputation of AI in health research going forward. As one oncologist I talked to put it, the reason Watson destroyed at Jeopardy but failed in cancer research was because we know the answers to Jeopardy. So if you want to have skills that continue to be valuable you have to keep learning things and you have to be in some of these more amorphous fields almost.

So, I want to share one example of how this has played out in the past. When ATMs were created the thought was that this would do away with bank tellers for good, right. Bank tellers did repetitive transactions and so you wouldn't need them anymore. But, in fact, as more ATMS came online there were more jobs for bank tellers. What happened was that each branch needed fewer tellers so each branch of a bank became cheaper and banks opened more branches so there were more tellers. But the job of teller changed completely. It was no longer someone who could do repetitive transactions. Rather, they had to learn marketing skills and customer service and have this much wider array of broad skills because those broader skills and integrating different types of information are what's difficult for computers.

The psychologist Robin Hogarth characterized domains of learning as going from the kind to the wicked. Kind learning environments were areas where patterns repeated. There was a wealth of previous data. There were clear rules and feedback was apparent. And in those kinds of areas like chess computers really thrive. On the other end of the spectrum are wicked environments where not all the information is clear. Rules don't necessarily repeat. People aren't waiting for each other to take turns. Feedback may be delayed. If you get it at all it may be inaccurate. And human behavior is involved. Those are areas where computers don't do as well. They require a lot of the so-called soft skills. How to deal with human behavior and how to adjust to things that are changing in real time and interpret signals that are very difficult to quantify. That's an area that's very, very difficult for computers but humans have a huge advantage. So, those kinds of soft skills are really important and will be for a long time to come.

  • In a rapidly changing work world it's critical to continue evolving your skills — this is especially true as automation's presence in the workforce increases.
  • Robots are good at working off of knowledge that we already know, however, they aren't that great when it comes to developing original ideas.
  • Though robots are good at jobs founded on patterns and data points, they currently don't excel when it comes to soft skills — that is, they have difficulty dealing with human behavior. On our end, soft skills help us make sense of chaotic environments where the dynamic human element is constantly in play.

This is what aliens would 'hear' if they flew by Earth

A Mercury-bound spacecraft's noisy flyby of our home planet.

Image source: sdecoret on Shutterstock/ESA/Big Think
Surprising Science
  • There is no sound in space, but if there was, this is what it might sound like passing by Earth.
  • A spacecraft bound for Mercury recorded data while swinging around our planet, and that data was converted into sound.
  • Yes, in space no one can hear you scream, but this is still some chill stuff.

First off, let's be clear what we mean by "hear" here. (Here, here!)

Sound, as we know it, requires air. What our ears capture is actually oscillating waves of fluctuating air pressure. Cilia, fibers in our ears, respond to these fluctuations by firing off corresponding clusters of tones at different pitches to our brains. This is what we perceive as sound.

All of which is to say, sound requires air, and space is notoriously void of that. So, in terms of human-perceivable sound, it's silent out there. Nonetheless, there can be cyclical events in space — such as oscillating values in streams of captured data — that can be mapped to pitches, and thus made audible.


Image source: European Space Agency

The European Space Agency's BepiColombo spacecraft took off from Kourou, French Guyana on October 20, 2019, on its way to Mercury. To reduce its speed for the proper trajectory to Mercury, BepiColombo executed a "gravity-assist flyby," slinging itself around the Earth before leaving home. Over the course of its 34-minute flyby, its two data recorders captured five data sets that Italy's National Institute for Astrophysics (INAF) enhanced and converted into sound waves.

Into and out of Earth's shadow

In April, BepiColombo began its closest approach to Earth, ranging from 256,393 kilometers (159,315 miles) to 129,488 kilometers (80,460 miles) away. The audio above starts as BepiColombo begins to sneak into the Earth's shadow facing away from the sun.

The data was captured by BepiColombo's Italian Spring Accelerometer (ISA) instrument. Says Carmelo Magnafico of the ISA team, "When the spacecraft enters the shadow and the force of the Sun disappears, we can hear a slight vibration. The solar panels, previously flexed by the Sun, then find a new balance. Upon exiting the shadow, we can hear the effect again."

In addition to making for some cool sounds, the phenomenon allowed the ISA team to confirm just how sensitive their instrument is. "This is an extraordinary situation," says Carmelo. "Since we started the cruise, we have only been in direct sunshine, so we did not have the possibility to check effectively whether our instrument is measuring the variations of the force of the sunlight."

When the craft arrives at Mercury, the ISA will be tasked with studying the planets gravity.

Magentosphere melody

The second clip is derived from data captured by BepiColombo's MPO-MAG magnetometer, AKA MERMAG, as the craft traveled through Earth's magnetosphere, the area surrounding the planet that's determined by the its magnetic field.

BepiColombo eventually entered the hellish mangentosheath, the region battered by cosmic plasma from the sun before the craft passed into the relatively peaceful magentopause that marks the transition between the magnetosphere and Earth's own magnetic field.

MERMAG will map Mercury's magnetosphere, as well as the magnetic state of the planet's interior. As a secondary objective, it will assess the interaction of the solar wind, Mercury's magnetic field, and the planet, analyzing the dynamics of the magnetosphere and its interaction with Mercury.

Recording session over, BepiColombo is now slipping through space silently with its arrival at Mercury planned for 2025.

Learn the Netflix model of high-performing teams

Erin Meyer explains the keeper test and how it can make or break a team.

  • There are numerous strategies for building and maintaining a high-performing team, but unfortunately they are not plug-and-play. What works for some companies will not necessarily work for others. Erin Meyer, co-author of No Rules Rules: Netflix and the Culture of Reinvention, shares one alternative employed by one of the largest tech and media services companies in the world.
  • Instead of the 'Rank and Yank' method once used by GE, Meyer explains how Netflix managers use the 'keeper test' to determine if employees are crucial pieces of the larger team and are worth fighting to keep.
  • "An individual performance problem is a systemic problem that impacts the entire team," she says. This is a valuable lesson that could determine whether the team fails or whether an organization advances to the next level.
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Photo by Martin Adams on Unsplash
Culture & Religion
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